Word-level correction of speech input

ABSTRACT

The subject matter of this specification can be implemented in, among other things, a computer-implemented method for correcting words in transcribed text including receiving speech audio data from a microphone. The method further includes sending the speech audio data to a transcription system. The method further includes receiving a word lattice transcribed from the speech audio data by the transcription system. The method further includes presenting one or more transcribed words from the word lattice. The method further includes receiving a user selection of at least one of the presented transcribed words. The method further includes presenting one or more alternate words from the word lattice for the selected transcribed word. The method further includes receiving a user selection of at least one of the alternate words. The method further includes replacing the selected transcribed word in the presented transcribed words with the selected alternate word.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.13/947,284, filed Jul. 22, 2013, which is a continuation of U.S.application Ser. No. 12/913,407, filed on Oct. 27, 2010, which claimsthe benefit of U.S. Provisional Application Ser. No. 61/292,440, filedon Jan. 5, 2010, the contents of which are incorporated by reference.

TECHNICAL FIELD

This instant specification relates to correcting one or more words intext transcribed from speech input to a computing device.

BACKGROUND

Transcription of speech input is an increasingly popular way ofinputting information into a computing device. This is even more truefor mobile computing devices, such as mobile telephones and smartphones,where the interfaces available to the user for making user inputs arenot as easy to manipulate as user interfaces in a desktop computer, suchas a full-size keyboard. For example, some mobile computing devices usea minimal hardware keyboard (e.g., a subset of the full QWERTYkeyboard), a virtual/software keyboard (e.g., a touchscreen keyboard),or even a twelve key telephone keypad (e.g., ITU-T text entry).Typically, these user input interfaces are smaller than traditionaldesktop user interfaces and users often type using their thumbs orotherwise hunt and peck while typing. This may account at least in partfor the increasing use of speech input to mobile computing devices.

SUMMARY

In general, this document describes correcting one or more words in texttranscribed from speech input to a computing device. In someimplementations, the computing device is a wireless mobile device, suchas a mobile telephone or a smartphone. The computing device receives aspeech input, e.g., from a user, and sends the speech input to atranscription system that is separate from the computing device. Thetranscription system transcribes the speech input and provides acorresponding word lattice to the computing device. The computing deviceallows the user to make corrections to one or more words in thetranscribed text using alternate words and/or phrases from the wordlattice.

In a first aspect, a computer-implemented method for correcting words intranscribed text includes receiving speech audio data from a microphonein a mobile computing device. The method further includes sending thespeech audio data from the mobile computing device to a transcriptionsystem. The method further includes receiving, at the mobile computingdevice, a word lattice transcribed from the speech audio data by thetranscription system. The method further includes presenting one or moretranscribed words from the word lattice on a display screen of themobile computing device. The method further includes receiving, at themobile computing device, a user selection of at least one of thepresented transcribed words. The method further includes in response toreceiving the user selection of the transcribed word, presenting one ormore alternate words on the display screen from the word lattice for theselected transcribed word. The method further includes receiving, at themobile computing device, a user selection of at least one of thealternate words. The method further includes in response to receivingthe user selection of the alternate word, replacing the selectedtranscribed word in the presented transcribed words with the selectedalternate word.

Implementations can include any, all, or none of the following features.The method can include in response to receiving the user selection ofthe transcribed word, presenting a remove command on the display screenfor the selected transcribed word; receiving, at the mobile computingdevice, a user selection of the remove command; and in response toreceiving the user selection of the remove command, removing theselected transcribed word from the presented transcribed words. Themethod can include presenting at least one alternate phrase on thedisplay screen from the word lattice for the presented transcribedwords; receiving, at the mobile computing device, a user selection ofthe alternate phrase; and in response to receiving the user selection ofthe alternate phrase, replacing the presented transcribed words with theselected alternate phrase. The method can include in response toreceiving the user selection of the alternate word or the removecommand, automatically selecting at least one new alternate phrase fromthe word lattice based on the selected alternate word or the removedtranscribed word; and replacing the presented alternate phrase with thenew alternate phrase. Receiving the user selection of the presented wordand the user selection of the alternate word can include receiving theuser selection of the presented word and the user selection of thealternate word through a touchscreen interface of the mobile computingdevice. The word lattice can include nodes corresponding to thetranscribed words and the alternate words, edges between the nodes thatidentify possible paths through the word lattice, and each path can havean associated probability of being correct. The method can includeidentifying the alternate words for the selected transcribed word fromone or more alternate paths between a beginning node and an ending nodeof the selected transcribed word in the word lattice. The method caninclude identifying the alternate phrase for the presented transcribedwords from at least one alternate path between a beginning node and anending node of the presented transcribed words in the word lattice.

In a second aspect, a computer program product, encoded on acomputer-readable medium, operable to cause one or more processors toperform operations for correcting words in transcribed text, theoperations include receiving speech audio data from a microphone in amobile computing device. The operations further include sending thespeech audio data from the mobile computing device to a transcriptionsystem. The operations further include receiving, at the mobilecomputing device, a word lattice transcribed from the speech audio databy the transcription system. The operations further include presentingone or more transcribed words from the word lattice on a display screenof the mobile computing device. The operations further includereceiving, at the mobile computing device, a user selection of at leastone of the presented transcribed words. The operations further includein response to receiving the user selection of the transcribed word,presenting one or more alternate words on the display screen from theword lattice for the selected transcribed word. The operations furtherinclude receiving, at the mobile computing device, a user selection ofat least one of the alternate words. The operations further include inresponse to receiving the user selection of the alternate word,replacing the selected transcribed word in the presented transcribedwords with the selected alternate word.

Implementations can include any, all, or none of the following features.The operations can include in response to receiving the user selectionof the transcribed word, presenting a remove command on the displayscreen for the selected transcribed word; receiving, at the mobilecomputing device, a user selection of the remove command; and inresponse to receiving the user selection of the remove command, removingthe selected transcribed word from the presented transcribed words. Theoperations can include presenting at least one alternate phrase on thedisplay screen from the word lattice for the presented transcribedwords; receiving, at the mobile computing device, a user selection ofthe alternate phrase; and in response to receiving the user selection ofthe alternate phrase, replacing the presented transcribed words with theselected alternate phrase. The operations can include in response toreceiving the user selection of the alternate word or the removecommand, automatically selecting at least one new alternate phrase fromthe word lattice based on the selected alternate word or the removedtranscribed word; and replacing the presented alternate phrase with thenew alternate phrase. Receiving the user selection of the presented wordand the user selection of the alternate word can include receiving theuser selection of the presented word and the user selection of thealternate word through a touchscreen interface of the mobile computingdevice. The word lattice can include nodes corresponding to thetranscribed words and the alternate words, edges between the nodes thatidentify possible paths through the word lattice, and each path can havean associated probability of being correct. The operations can includeidentifying the alternate words for the selected transcribed word fromone or more alternate paths between a beginning node and an ending nodeof the selected transcribed word in the word lattice. The operations caninclude identifying the alternate phrase for the presented transcribedwords from at least one alternate path between a beginning node and anending node of the presented transcribed words in the word lattice.

In a third aspect, a computer-implemented system for correcting words intranscribed text includes a transcription system operable to receivespeech audio data and in response transcribe the speech audio data intoa word lattice. The system further includes a mobile computing devicethat includes a microphone operable to receive speech audio and generatethe speech audio data, a network interface operable to send the speechaudio data to the transcription system and in response receive the wordlattice from the transcription system, a display screen operable topresent one or more transcribed words from the word lattice, a userinterface operable to receive a user selection of at least one of thetranscribed words, one or more processors and a memory storinginstructions that when executed by the processors perform operations topresent one or more alternate words on the display screen from the wordlattice for the selected transcribed word, receive a user selection ofat least one of the alternate words, and replace the selectedtranscribed word in the presented transcribed words with the selectedalternate word.

The systems and techniques described here may provide one or more of thefollowing advantages. First, a system can make a correction to one ormore words in transcribed text with a minimum of user inputs, such asone, two, or three user inputs. Second, a system can providetranscription of a speech input into text at a remote transcriptionsystem without, or with a minimum of, additional communication to theremote transcription system during correction of one or more words inthe transcribed text. Third, a system can provide efficient userselection of corrections to transcribed text in a computing device withlimited input interfaces, such as a small touchscreen.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features andadvantages will be apparent from the description and drawings, and fromthe claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic diagram that shows an example of a system forcorrecting one or more words in transcribed text.

FIG. 2 is a block diagram that shows an example of a mobile computingdevice for correcting one or more words in transcribed text.

FIGS. 3A-B are examples of word lattices used for correcting one or morewords in transcribed text.

FIGS. 4A-D are examples of graphical user interfaces for correcting oneor more words in transcribed text.

FIG. 5 is a flow chart that shows an example of a process for correctingone or more words in transcribed text.

FIG. 6 shows an example of a computing device and a mobile computingdevice that can be used in connection with computer-implemented methodsand systems described in this document.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

FIG. 1 is a schematic diagram that shows an example of a system 100 forcorrecting one or more words in transcribed text. In general, the systemallows a user's device to send audio data of speech to a server system,and for the server system to send back an arrangement of possiblesolutions for transcribing the speech, so that if a first suggestedsolution is not accurate, the user can easily substitute other words orsets of words that were determined by the server system to be otherpossible solutions.

The system 100 includes a mobile computing device 102 in communicationwith a transcription system 104 over a network 106. The mobile computingdevice 102 receives a speech audio input from a user and converts thespeech audio into a speech data output 108. The mobile computing device102 sends the speech data output 108 to the transcription system 104over the network 106. The transcription system 104 transcribes thespeech data output 108 into a plurality of words and arranges the wordsin a word lattice 110. The word lattice 110 includes a most likely orbest hypothesis for the transcription of the speech data output 108 aswell as alternate transcriptions or hypotheses. The transcription system104 sends the word lattice 110 to the mobile computing device 102.

The mobile computing device 102 presents the most likely transcriptionfrom the word lattice 110 to the user. The mobile computing device 102then receives one or more word selections 112 from the user, presentscorresponding alternate words for the selected words, and receives oneor more alternate selections 114 from the user. The word selections 112indicate one or more incorrectly transcribed words in the transcribedtext presented to the user. In some implementations, the alternate wordsare the next best hypotheses for the incorrect words. In response to thealternate selections 114, the mobile computing device 102 replaces theincorrect words in the presented transcribed text with the selectedalternate words.

In some implementations, the mobile computing device 102 also presentsone or more alternate phrases for the transcribed text. For example, thealternate phrase may be a next best hypothesis for transcription of thespeech data output 108 or a portion of the speech data output 108 thatincludes multiple words. The mobile computing device 102 can receive aselection of an alternate phrase from the user and replaces thecorresponding portion of the presented transcribed text with theselected alternate phrase.

In some implementations, the mobile computing device 102 is a mobiletelephone or smartphone and includes a limited user input interface,such as a small QWERTY hardware keyboard, a small touchscreen, or anumeric keypad. The mobile computing device 102 accesses the network 106using a wireless connection, such as a cellular telephone dataconnection, a Wi-Fi connection, or other wireless connection that can beused for sending data to and receiving data from the transcriptionsystem 104.

In some implementations, the network 106 includes one or more networks,such as a local area network, a wide area network, and/or the Internet.One or more of the networks in the network 106 may be wireless, such asa cellular telephone network or a Wi-Fi network.

The transcription system 104 includes a speech recognizer thattranscribes the speech data output 108 into the word lattice 110. Ingeneral, the word lattice 110 includes multiple hypotheses for thetranscription of the speech data output 108. In some implementations,the word lattice 110 includes one or more weighting factors orprobabilities that a particular word occurs at a particular location inthe transcribed text. Each hypothesis for the transcription of theutterance represents a possible path through the word lattice 110. Insome implementations, branch points from one word to the next in ahypothesis depend on the other words in the hypothesis. For example, aparticular word in the word lattice 110 may have multiple weights orprobabilities that depend upon the other words included in thehypothesis. In addition, the word lattice 110 may include all of thepossible hypotheses for the set of words included in the word lattice110 or a subset of the most probable combinations of words from the wordlattice 110. The mobile computing device 102 selects the most probablepath through the word lattice 110 and presents that hypothesis to theuser.

FIG. 2 is a block diagram that shows an example of a mobile computingdevice 200 for correcting one or more words in transcribed text. Themobile computing device 200 includes a word correction module 202 thatis responsible for presenting text transcribed from a user utterance andfor receiving one or more user inputs to correct the transcribed text.

In particular, the mobile computing device 200 includes a speech inputinterface 204 that receives a speech audio input 206 from a user. Forexample, the speech input interface 204 can be a microphone thatconverts the sounds in the utterance from the user into a speech dataoutput 208. The speech input interface 204 passes the speech data output208 to the word correction module 202 and the word correction module 202sends the speech data output 208 to a transcription system.

The transcription system performs a speech recognition operation on thespeech data output 208 to generate a word lattice 210. The transcriptionsystem sends the word lattice 210 to the mobile computing device 200.

The word correction module 202 receives the word lattice 210 andpresents a transcribed text 212 from the word lattice 210 in a displayinterface 214. In some implementations, the display interface 214 is ahardware display screen, such as a liquid crystal display (LCD) screen.The transcribed text 212 being presented includes multiple words fromthe word lattice 210 and the transcribed text 212 includes one or morewords to be corrected by the user. The word correction module 202receives a selection 216 from the user of word in the transcribed text212 that is incorrect (e.g., not what the user spoke). The wordcorrection module 202 receives the selection 216 through a user inputinterface 218, such as a touchscreen, a track ball or other pointingdevice, or a keyboard.

The word correction module 202 presents one or more alternate words 220for the selection 216. The word correction module 202 displays thealternate words 220 using the display interface 214. The word correctionmodule 202 receives a selection 222 of one of the presented alternatewords from the user through the user input interface 218. The wordcorrection module 202 replaces the selection 216 from the transcribedtext 212 with the selection 222 from the alternate words and presentsthe updated transcribed text to the user in the display interface 214.

FIG. 3A is an example of a word lattice 300 used for correcting one ormore words in transcribed text. The word lattice 300 is represented hereas a finite state transducer. The word lattice 300 includes one or morenodes 302 a-g that correspond to the possible boundaries between words.The word lattice 300 includes multiple edges 304 a-l for the possiblewords in the transcription hypotheses that result from the word lattice300. In addition, each of the edges 304 a-l can have one or more weightsor probabilities of that edge being the correct edge from thecorresponding node. The weights are determined by the transcriptionsystem and can be based on, for example, a confidence in the matchbetween the speech data and the word for that edge and how well the wordfits grammatically and/or lexically with other words in the word lattice300.

For example, initially, the most probable path through the word lattice300 may include the edges 304 c, 304 e, 304 i, and 304 k, which have thetext “we're coming about 11:30.” A second best path may include theedges 304 d, 304 h, 304 j, and 304 l, which have the text “deer huntingscouts 7:30.”

Each pair of nodes may have one or more paths corresponding to thealternate words in the various transcription hypotheses. For example,the initial most probable path between the node pair beginning at thenode 302 a and ending at the node 302 c is the edge 304 c “we're”. Thispath has alternate paths that include the edges 304 a-b “we are” and theedge 304 d “deer”. Accordingly, the edge 304 e “coming” has alternatewords that include the edges 304 f-g “come at” and the edge 304 h“hunting”. The edge 304 i “about” has an alternate word that includesthe edge 304 j “scouts” and the edge 304 k “11:30” has an alternate wordthat includes the edge 304 l “7:30”.

FIG. 3B is an example of a word lattice 350 used for correcting one ormore words in transcribed text. The word lattice 350 is a hierarchy. Theword lattice 350 includes multiple nodes 352 a-l that represent thewords in the various hypotheses for the transcribed text. The edgesbetween the nodes 352 a-l show that the possible hypotheses include thenodes 352 c, 352 e, 352 i, and 352 k “we're coming about 11:30”, thenodes 352 a, 352 b, 352 e, 352 i, and 352 k “we are coming about 11:30”,the nodes 352 a, 352 b, 352 f, 352 g, 352 i, and 352 k “we are come atabout 11:30”, the nodes 352 d, 352 f, 352 g, 352 i, and 352 k “deer comeat about 11:30”, the nodes 352 d, 352 h, 352 j, and 352 k “deer huntingscouts 11:30”, and the nodes 352 d, 352 h, 352 j, and 352 l “deerhunting scouts 7:30”.

Again, the edges between the nodes 352 a-l may have associated weightsor probabilities based on the confidence in the speech recognition andthe grammatical/lexical analysis of the resulting text. In this example,“we're coming about 11:30” may currently be the best hypothesis and“deer hunting scouts 7:30” may be the next best hypothesis. One or moredivisions 354 a-d can be made in the word lattice 350 that group a wordand its alternates together. For example, the division 354 a includesthe word “we're” and the alternates “we are” and “deer”. The division354 b includes the word “coming” and the alternates “come at” and“hunting”. The division 354 c includes the word “about” and thealternate “scouts” and the division 354 d includes the word “11:30” andthe alternate “7:30”.

As a user selects words from the best hypothesis for correction andalternates from the other hypotheses to replace the incorrect words, oneof the other hypotheses may become the best hypothesis. For example, ifthe user selects “we're” and then the alternate “deer” to replace“we're”, then the “deer hunting scouts 7:30” may become the besthypothesis.

In some implementations, the word correction module only presents and/orallows the user to select alternates for which an edge exists to theother words in the transcribed text. For example, if “we're coming about11:30” is currently presented as the best hypothesis, the wordcorrection module may present “we are” as an alternate for “we're” butnot “deer” because “deer” does not have an edge that connects to theremainder of the transcribed text “ . . . coming about 11:30”. The words“we are” do have an edge to “ . . . coming about 11:30” and aretherefore included in the list of alternates for “we're”. In anotherexample, if the user selects the word “coming” for correction, the wordcorrection module may expand the selection to include “we're coming” andthen present alternates that include “we are come at” and “deer comeat”.

FIG. 4A is an example of a GUI 400 for correcting one or more words intranscribed text. The GUI 400 may be associated with an application thatreceives a text input, such as an instant message application, an emailapplication, or a word processor application. The GUI 400 includes atext input area 402 and a keyboard 404 for inputting text into the textinput area 402. In some implementations, the keyboard 404 is atouchscreen keyboard. In some implementations, a computing device thatprovides the GUI 400 can include a physical keyboard for making inputsinto the text input area 402. In addition, a computing device thatprovides the GUI 400 can receive a voice or speech input. For example,the keyboard 404 can include a control or icon to initiatespeech-to-text input into the text input area 402. The word correctionmodule sends the received speech data to the transcription system andreceives the word lattice.

The GUI 400 presents a best hypothesis “we're coming about 11:30” in thetext input area 402. A user can request that a word be corrected byselecting the word. For example, the user can make a selection 406 ofthe word “we're” by pressing on the touchscreen. Alternatively, the GUI400 may have an associated pointing device or other navigation controlsto select a word in the text input area 402.

The GUI presents a next best hypothesis “Deer hunting scouts 7:30” in analternate phrase control 408. A user can select the alternate phrasecontrol 408 to replace the transcribed text in the text input area 402with the text shown in the alternate phrase control 408.

FIG. 4B is an example of a GUI 420 for correcting one or more words intranscribed text. The GUI 420 shows a list 422 of alternate words fromthe word lattice for the selected word “we're”. The list 422 includesthe alternates “we are” and “deer”. The list 422 also includes a removecontrol for removing a word from the text input area 402 withoutreplacing it with an alternate. Here, the user makes a selection 424 onthe remove control to request that the GUI 420 remove the word “we're”from the text input area 402.

FIG. 4C is an example of a GUI 440 for correcting one or more words intranscribed text. The word correction module has updated the GUI 440 tono longer include the word “we're” in the transcription hypothesispresented in the text input area 402. In addition, the word correctionmodule has updated the alternate phrase control 408 to include a newnext best hypothesis “Come at about 11:30.” based on the current besthypothesis in the text input area 402 resulting from the correction madeby the user. The user can make a selection 442 on the alternate phrasecontrol 408 to request that the text in the text input area 402 bereplaced with “come at about 11:30”.

FIG. 4D is an example of a GUI 460 for correcting one or more words intranscribed text. The word correction module has updated the GUI 460 toinclude the new best transcription hypothesis “Come at about 11:30.”requested by the user's selection of the alternate phrase control 408.

In some implementations, the word correction module allows a user tocorrect a word by making only two simple user inputs. For example, theuser may touch the screen to select an incorrect word and then touch thescreen a second time to select an alternate to replace the incorrectword.

In some implementations, the word correction module can correct one ormore words in response to a single user input. For example, the user canselect the alternate phrase control 408 to replace the best hypothesiswith the next best hypothesis. In another example, where only onealternative word exists, the word correction module may automaticallyreplace an incorrect word in response to the selection of the incorrectword without providing a list of alternates. In a further example, wherethe probability of an alternate being correct is significantly greaterthan the other alternates, the word correction module may automaticallyreplace an incorrect word with the best alternate in response to theselection of the incorrect word without providing a list of alternates.Significantly greater may include for example, a best alternate with aprobability near one hundred percent and other alternates withprobabilities near zero or a best alternate that is several times moreprobable than the next best alternate. In some implementations, a longpress on a word may indicate that the word should be removed from thetext input area 402 and the hypothesis. Alternatively, a long press onan incorrect word may indicate a request to replace the incorrect wordwith the next best alternate.

FIG. 5 is a flow chart that shows an example of a process 500 forcorrecting one or more words in transcribed text. The process 500 may beperformed, for example, by a system such as the system 100, the mobilecomputing device 200, the word lattice 300, and/or the GUIs 400, 420,440, and 460. For clarity of presentation, the description that followsuses the system 100, the mobile computing device 200, the word lattice300, and/or the GUIs 400, 420, 440, and 460 as the basis of examples fordescribing the process 500. However, another system, or combination ofsystems, may be used to perform the process 500.

The process 500 begins with receiving (502) speech audio data from amicrophone in a mobile computing device. For example, a user may inputan utterance into a microphone on a cellular telephone or smartphone.

The process 500 sends (504) the speech audio data from the mobilecomputing device to a transcription system. For example, the mobilecomputing device 102 can send the speech data output 108 to thetranscription system 104.

The process 500 receives (506), at the mobile computing device, a wordlattice transcribed from the speech audio data by the transcriptionsystem. For example, the mobile computing device 200 can receive theword lattice 210 transcribed from the speech data output 208.

The process 500 presents (508) one or more transcribed words from theword lattice on a display screen of the mobile computing device. Forexample, the word correction module 202 can present the transcribed text212 in the GUI 400.

If the process 500 receives (510), at the mobile computing device, auser selection of at least one of the presented transcribed words, thenin response to receiving the user selection of the transcribed word, theprocess 500 presents (512) one or more alternate words on the displayscreen from the word lattice for the selected transcribed word. Forexample, the word correction module 202 can receive the selection 406 ofthe transcribed word “we're” and in response present the list 422 ofalternate words.

The process 500 receives (514), at the mobile computing device, a userselection of at least one of the alternate words. For example, the wordcorrection module 202 can receive the selection 424 of the removecontrol or a selection of one or more of the alternate words “we are”and “deer” in the list 422.

In response to receiving the user selection of the alternate word, theprocess 500 replaces (508) the selected transcribed word in thepresented transcribed words with the selected alternate word. Forexample, the word correction module 202 can present the updatedtranscribed text “coming about 11:30” in the text input area 402 of theGUI 440.

FIG. 6 shows an example of a computing device 600 and a mobile computingdevice that can be used to implement the techniques described here. Thecomputing device 600 is intended to represent various forms of digitalcomputers, such as laptops, desktops, workstations, personal digitalassistants, servers, blade servers, mainframes, and other appropriatecomputers. The mobile computing device is intended to represent variousforms of mobile devices, such as personal digital assistants, cellulartelephones, smart-phones, and other similar computing devices. Thecomponents shown here, their connections and relationships, and theirfunctions, are meant to be exemplary only, and are not meant to limitimplementations of the inventions described and/or claimed in thisdocument.

The computing device 600 includes a processor 602, a memory 604, astorage device 606, a high-speed interface 608 connecting to the memory604 and multiple high-speed expansion ports 610, and a low-speedinterface 612 connecting to a low-speed expansion port 614 and thestorage device 606. Each of the processor 602, the memory 604, thestorage device 606, the high-speed interface 608, the high-speedexpansion ports 610, and the low-speed interface 612, are interconnectedusing various busses, and may be mounted on a common motherboard or inother manners as appropriate. The processor 602 can process instructionsfor execution within the computing device 600, including instructionsstored in the memory 604 or on the storage device 606 to displaygraphical information for a GUI on an external input/output device, suchas a display 616 coupled to the high-speed interface 608. In otherimplementations, multiple processors and/or multiple buses may be used,as appropriate, along with multiple memories and types of memory. Also,multiple computing devices may be connected, with each device providingportions of the necessary operations (e.g., as a server bank, a group ofblade servers, or a multi-processor system).

The memory 604 stores information within the computing device 600. Insome implementations, the memory 604 is a volatile memory unit or units.In some implementations, the memory 604 is a non-volatile memory unit orunits. The memory 604 may also be another form of computer-readablemedium, such as a magnetic or optical disk.

The storage device 606 is capable of providing mass storage for thecomputing device 600. In some implementations, the storage device 606may be or contain a computer-readable medium, such as a floppy diskdevice, a hard disk device, an optical disk device, or a tape device, aflash memory or other similar solid state memory device, or an array ofdevices, including devices in a storage area network or otherconfigurations. The computer program product may also containinstructions that, when executed, perform one or more methods, such asthose described above. The computer program product can also be tangiblyembodied in a computer- or machine-readable medium, such as the memory604, the storage device 606, or memory on the processor 602.

The high-speed interface 608 manages bandwidth-intensive operations forthe computing device 600, while the low-speed interface 612 manageslower bandwidth-intensive operations. Such allocation of functions isexemplary only. In some implementations, the high-speed interface 608 iscoupled to the memory 604, the display 616 (e.g., through a graphicsprocessor or accelerator), and to the high-speed expansion ports 610,which may accept various expansion cards (not shown). In theimplementation, the low-speed interface 612 is coupled to the storagedevice 606 and the low-speed expansion port 614. The low-speed expansionport 614, which may include various communication ports (e.g., USB,Bluetooth, Ethernet, wireless Ethernet) may be coupled to one or moreinput/output devices, such as a keyboard, a pointing device, a scanner,or a networking device such as a switch or router, e.g., through anetwork adapter.

The computing device 600 may be implemented in a number of differentforms, as shown in the figure. For example, it may be implemented as astandard server 620, or multiple times in a group of such servers. Inaddition, it may be implemented in a personal computer such as a laptopcomputer 622. It may also be implemented as part of a rack server system624. Alternatively, components from the computing device 600 may becombined with other components in a mobile device (not shown), such as amobile computing device 650. Each of such devices may contain one ormore of the computing device 600 and the mobile computing device 650,and an entire system may be made up of multiple computing devicescommunicating with each other.

The mobile computing device 650 includes a processor 652, a memory 664,an input/output device such as a display 654, a communication interface666, and a transceiver 668, among other components. The mobile computingdevice 650 may also be provided with a storage device, such as amicro-drive or other device, to provide additional storage. Each of theprocessor 652, the memory 664, the display 654, the communicationinterface 666, and the transceiver 668, are interconnected using variousbuses, and several of the components may be mounted on a commonmotherboard or in other manners as appropriate.

The processor 652 can execute instructions within the mobile computingdevice 650, including instructions stored in the memory 664. Theprocessor 652 may be implemented as a chipset of chips that includeseparate and multiple analog and digital processors. The processor 652may provide, for example, for coordination of the other components ofthe mobile computing device 650, such as control of user interfaces,applications run by the mobile computing device 650, and wirelesscommunication by the mobile computing device 650.

The processor 652 may communicate with a user through a controlinterface 658 and a display interface 656 coupled to the display 654.The display 654 may be, for example, a TFT (Thin-Film-Transistor LiquidCrystal Display) display or an OLED (Organic Light Emitting Diode)display, or other appropriate display technology. The display interface656 may comprise appropriate circuitry for driving the display 654 topresent graphical and other information to a user. The control interface658 may receive commands from a user and convert them for submission tothe processor 652. In addition, an external interface 662 may providecommunication with the processor 652, so as to enable near areacommunication of the mobile computing device 650 with other devices. Theexternal interface 662 may provide, for example, for wired communicationin some implementations, or for wireless communication in otherimplementations, and multiple interfaces may also be used.

The memory 664 stores information within the mobile computing device650. The memory 664 can be implemented as one or more of acomputer-readable medium or media, a volatile memory unit or units, or anon-volatile memory unit or units. An expansion memory 674 may also beprovided and connected to the mobile computing device 650 through anexpansion interface 672, which may include, for example, a SIMM (SingleIn Line Memory Module) card interface. The expansion memory 674 mayprovide extra storage space for the mobile computing device 650, or mayalso store applications or other information for the mobile computingdevice 650. Specifically, the expansion memory 674 may includeinstructions to carry out or supplement the processes described above,and may include secure information also. Thus, for example, theexpansion memory 674 may be provide as a security module for the mobilecomputing device 650, and may be programmed with instructions thatpermit secure use of the mobile computing device 650. In addition,secure applications may be provided via the SIMM cards, along withadditional information, such as placing identifying information on theSIMM card in a non-hackable manner.

The memory may include, for example, flash memory and/or NVRAM memory(non-volatile random access memory), as discussed below. The computerprogram product contains instructions that, when executed, perform oneor more methods, such as those described above. The computer programproduct can be a computer- or machine-readable medium, such as thememory 664, the expansion memory 674, or memory on the processor 652. Insome implementations, the computer program product can be received in apropagated signal, for example, over the transceiver 668 or the externalinterface 662.

The mobile computing device 650 may communicate wirelessly through thecommunication interface 666, which may include digital signal processingcircuitry where necessary. The communication interface 666 may providefor communications under various modes or protocols, such as GSM voicecalls (Global System for Mobile communications), SMS (Short MessageService), EMS (Enhanced Messaging Service), or MMS messaging (MultimediaMessaging Service), CDMA (code division multiple access), TDMA (timedivision multiple access), PDC (Personal Digital Cellular), WCDMA(Wideband Code Division Multiple Access), CDMA2000, or GPRS (GeneralPacket Radio Service), among others. Such communication may occur, forexample, through the transceiver 668 using a radio-frequency. Inaddition, short-range communication may occur, such as using aBluetooth, WiFi, or other such transceiver (not shown). In addition, aGPS (Global Positioning System) receiver module 670 may provideadditional navigation- and location-related wireless data to the mobilecomputing device 650, which may be used as appropriate by applicationsrunning on the mobile computing device 650.

The mobile computing device 650 may also communicate audibly using anaudio codec 660, which may receive spoken information from a user andconvert it to usable digital information. The audio codec 660 maylikewise generate audible sound for a user, such as through a speaker,e.g., in a handset of the mobile computing device 650. Such sound mayinclude sound from voice telephone calls, may include recorded sound(e.g., voice messages, music files, etc.) and may also include soundgenerated by applications operating on the mobile computing device 650.

The mobile computing device 650 may be implemented in a number ofdifferent forms, as shown in the figure. For example, it may beimplemented as a cellular telephone 680. It may also be implemented aspart of a smart-phone 682, personal digital assistant, or other similarmobile device.

Various implementations of the systems and techniques described here canbe realized in digital electronic circuitry, integrated circuitry,specially designed ASICs (application specific integrated circuits),computer hardware, firmware, software, and/or combinations thereof.These various implementations can include implementation in one or morecomputer programs that are executable and/or interpretable on aprogrammable system including at least one programmable processor, whichmay be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor, and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms machine-readable medium andcomputer-readable medium refer to any computer program product,apparatus and/or device (e.g., magnetic discs, optical disks, memory,Programmable Logic Devices (PLDs)) used to provide machine instructionsand/or data to a programmable processor, including a machine-readablemedium that receives machine instructions as a machine-readable signal.The term machine-readable signal refers to any signal used to providemachine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniquesdescribed here can be implemented on a computer having a display device(e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor)for displaying information to the user and a keyboard and a pointingdevice (e.g., a mouse or a trackball) by which the user can provideinput to the computer. Other kinds of devices can be used to provide forinteraction with a user as well; for example, feedback provided to theuser can be any form of sensory feedback (e.g., visual feedback,auditory feedback, or tactile feedback); and input from the user can bereceived in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in acomputing system that includes a back end component (e.g., as a dataserver), or that includes a middleware component (e.g., an applicationserver), or that includes a front end component (e.g., a client computerhaving a graphical user interface or a Web browser through which a usercan interact with an implementation of the systems and techniquesdescribed here), or any combination of such back end, middleware, orfront end components. The components of the system can be interconnectedby any form or medium of digital data communication (e.g., acommunication network). Examples of communication networks include alocal area network (LAN), a wide area network (WAN), and the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

Although a few implementations have been described in detail above,other modifications are possible. In addition, the logic flows depictedin the figures do not require the particular order shown, or sequentialorder, to achieve desirable results. In addition, other steps may beprovided, or steps may be eliminated, from the described flows, andother components may be added to, or removed from, the describedsystems. Accordingly, other implementations are within the scope of thefollowing claims.

What is claimed is:
 1. A computer-implemented method comprising:providing a first transcription of an utterance, wherein the firsttranscription of the utterance includes one or more words; receivingdata indicating a selection of a word from among the one or more wordsincluded in the first transcription of the utterance; in response toreceiving the data indicating the selection of the word, providing oneor more alternate words for the selected word; receiving data indicatinga selection of a particular alternate word from among the one or morealternate words for the selected word; selecting a second transcriptionof the utterance that includes the particular alternate word and that isidentified as having a speech recognition confidence measure value thatsatisfies one or more criteria; and replacing the first transcription ofthe utterance with the second transcription of the utterance.
 2. Thecomputer-implemented method of claim 1, wherein the one or more wordsare selected from a hierarchical word lattice.
 3. Thecomputer-implemented method of claim 2, wherein the hierarchical wordlattice comprises nodes corresponding to the one or more words of thefirst transcription of the utterance and words of the secondtranscription of the utterance, and edges between the nodes thatidentify possible paths through the word lattice, wherein each path hasan associated probability of being correct.
 4. The computer-implementedmethod of claim 3, wherein providing the one or more alternate words forthe selected word comprises: identifying one or more alternate words forthe selected word for which an edge exists to the other words of thefirst transcription in the hierarchical word lattice; and providing theone or more alternate words for the selected word for which an edgeexists to the other words of the first transcription as the one or morealternate words for the selected word, without providing other wordsfrom the hierarchical word lattice for which an edge does not exist tothe other words of the first transcription as alternate words for theselected word.
 5. The computer-implemented method of claim 1, whereinthe first transcription of the utterance is a transcription of theutterance that is identified as having a highest speech recognizerconfidence measure value among all transcriptions of the utterance. 6.The computer-implemented method of claim 1, wherein the secondtranscription of the utterance is a transcription of the utterance thatincludes the particular alternate word and that is identified as havinga highest speech recognizer confidence measure value among alltranscriptions of the utterance that include the particular alternateword.
 7. The computer-implemented method of claim 1, wherein: the firsttranscription of the utterance and the second transcription of theutterance are provided for output at a touchscreen display of acomputing device; and the data indicating the selection of the word fromamong the one or more words included in the first transcription and thedata indicating the selection of the particular alternate word fromamong the one or more alternate words for the selected word are receivedin response to user input at the touchscreen display of the computingdevice.
 8. A system for correcting words in transcribed text, the systemcomprising: an automated speech recognizer operable to receive speechaudio data and in response transcribe the speech audio data in a wordlattice; and a computing device comprising: a microphone operable toreceive speech audio and generate the speech audio data, a networkinterface operable to send the speech audio data to the automated speechrecognizer and in response receive the word lattice from the automatedspeech recognizer, a display screen operable to present one or moretranscribed words from the word lattice, a user interface operable toreceive a user selection of at least one of the transcribed words, andone or more processors and a memory storing instructions that whenexecuted by the processors cause the computing device to performoperations to: provide a first transcription of an utterance, whereinthe first transcription of the utterance includes one or more words;receive data indicating a selection of a word from among the one or morewords included in the first transcription of the utterance; in responseto receiving the data indicating the selection of the word, provide oneor more alternate words for the selected word; receive data indicating aselection of a particular alternate word from among the one or morealternate words for the selected word; select a second transcription ofthe utterance that includes the particular alternate word and that isidentified as having a speech recognition confidence measure value thatsatisfies one or more criteria; and replace the first transcription ofthe utterance with the second transcription of the utterance.
 9. Thesystem of claim 8, wherein the one or more words are selected from ahierarchical word lattice.
 10. The system of claim 9, wherein thehierarchical word lattice comprises nodes corresponding to the one ormore words of the first transcription of the utterance and words of thesecond transcription of the utterance, and edges between the nodes thatidentify possible paths through the word lattice, wherein each path hasan associated probability of being correct.
 11. The system of claim 10,wherein providing the one or more alternate words for the selected wordcomprises: identifying one or more alternate words for the selected wordfor which an edge exists to the other words of the first transcriptionin the hierarchical word lattice; and providing the one or morealternate words for the selected word for which an edge exists to theother words of the first transcription as the one or more alternatewords for the selected word, without providing other words from thehierarchical word lattice for which an edge does not exist to the otherwords of the first transcription as alternate words for the selectedword.
 12. The system of claim 8, wherein the first transcription of theutterance is a transcription of the utterance that is identified ashaving a highest speech recognizer confidence measure value among alltranscriptions of the utterance.
 13. The system of claim 8, wherein thesecond transcription of the utterance is a transcription of theutterance that includes the particular alternate word and that isidentified as having a highest speech recognizer confidence measurevalue among all transcriptions of the utterance that include theparticular alternate word.
 14. The system of claim 8, wherein: the firsttranscription of the utterance and the second transcription of theutterance are provided for output at a touchscreen display of acomputing device; and the data indicating the selection of the word fromamong the one or more words included in the first transcription and thedata indicating the selection of the particular alternate word fromamong the one or more alternate words for the selected word are receivedin response to user input at the touchscreen display of the computingdevice.
 15. A computer program product, encoded on a non-transitorycomputer-readable medium, operable to cause one or more processors toperform operations for correcting words in transcribed text, theoperations comprising: providing a first transcription of an utterance,wherein the first transcription of the utterance includes one or morewords; receiving data indicating a selection of a word from among theone or more words included in the first transcription of the utterance;in response to receiving the data indicating the selection of the word,providing one or more alternate words for the selected word; receivingdata indicating a selection of a particular alternate word from amongthe one or more alternate words for the selected word; selecting asecond transcription of the utterance that includes the particularalternate word and that is identified as having a speech recognitionconfidence measure value that satisfies one or more criteria; andreplacing the first transcription of the utterance with the secondtranscription of the utterance.
 16. The computer program product ofclaim 15, wherein the one or more words are selected from a hierarchicalword lattice.
 17. The computer program product of claim 16, wherein thehierarchical word lattice comprises nodes corresponding to the one ormore words of the first transcription of the utterance and words of thesecond transcription of the utterance, and edges between the nodes thatidentify possible paths through the word lattice, wherein each path hasan associated probability of being correct.
 18. The computer programproduct of claim 17, wherein providing the one or more alternate wordsfor the selected word comprises: identifying one or more alternate wordsfor the selected word for which an edge exists to the other words of thefirst transcription in the hierarchical word lattice; and providing theone or more alternate words for the selected word for which an edgeexists to the other words of the first transcription as the one or morealternate words for the selected word, without providing other wordsfrom the hierarchical word lattice for which an edge does not exist tothe other words of the first transcription as alternate words for theselected word.
 19. The computer program product of claim 15, wherein thefirst transcription of the utterance is a transcription of the utterancethat is identified as having a highest speech recognizer confidencemeasure value among all transcriptions of the utterance.
 20. Thecomputer program product of claim 15, wherein the second transcriptionof the utterance is a transcription of the utterance that includes theparticular alternate word and that is identified as having a highestspeech recognizer confidence measure value among all transcriptions ofthe utterance that include the particular alternate word.